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depth Information based Image Restoration Method for Rotors 8

Depth Information based Image Restoration Method for Rotors

引用

8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

作者： Chung, Yi-Hao Yu, Chao-Wei Wen, Bo-Rui Chen, Yen-Lin National Taipei University Of Technology Dept. Computer Science And Information Engineering Taipei Taiwan

ISBN: (纸本)9781665433280

This paper presents a new depth information based image restoration method (DIBIRM) for rotors. The restoration method applies 3D sensor to obtain amplitude and depth image for a rotor. The overexposed areas can be detected by using depth data, and the mean value of amplitude images can be used to repair overexposed pixels. Experimental results showed that our proposed mothed improved effectiveness and robustness to rotor image restoration in online, real-time manufacturing automation system. © 2021 IEEE.

关键词： Image reconstruction

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Innovative Approaches to Dental Age Estimation: A Comprehensive Review of CNN Technologies and Ethical Issue

Innovative Approaches to Dental Age Estimation: A Comprehens...

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Data Intelligence and Cognitive Informatics (ICDICI), International Conference on

作者： I. Domilin Shyni Sheeja Herobin Rani C I. Rexiline Sheeba Mahizha S I Dept. Of Computer Science and Engineering DMI Engineering College Aralvoimozhi India Dept. Of Electronics and Communication Engineering St.Xavier’s Catholic College of Engineering Nagercoil India Dept. Of Electronics and Communication Engineering Sathyabama Institute of Technology and Science Chennai India Dept. Of Information Technology St.Xavier’s Catholic College of Engineering Nagercoil India

ISBN: (数字)9798350389609

ISBN: (纸本)9798350389616

Estimating dental age is crucial in multiple disciplines, such as forensic science, orthodontics, and pediatric dentistry. Traditional methods, while effective, often involve manual processes and subjective judgment. Recent advancements in Convolutional Neural Networks (CNNs) have introduced innovative approaches that promise greater accuracy and efficiency. This comprehensive review examines the latest CNN technologies applied to dental age estimation, highlighting their methodologies, performance, and advancements. Key aspects covered include the development and optimization of CNN architectures, the role of data preprocessing and augmentation, and the impact of these technologies on predictive accuracy. Additionally, the review addresses critical ethical issues associated with the implementation of CNNs in dental age estimation, such as data privacy, potential biases, and the implications of automated decision-making in sensitive contexts. By integrating insights from current research and practical applications, this review provides a thorough understanding of both the technological innovations and ethical considerations driving progress in determining dental age .

关键词： Ethics Technological innovation Accuracy Reviews Neural networks Estimation Manuals Dentistry Convolutional neural networks Optimization

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Metasurface-Based Low-Dispersive Leaky-Wave Antenna

Metasurface-Based Low-Dispersive Leaky-Wave Antenna

引用

2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2023

作者： Mahmoud, Adham Ettorre, Mauro Garcia, Jorge Ruiz Quevedo-Teruel, Oscar Grbic, Anthony Univ Rennes Institut d'Electronique et de Telecommunications de Rennes Cnrs Ietr Umr 6164 Rennes35000 France Michigan State University Electrical and Computer Engineering East LansingMI48824 United States University of Michigan Dept. of Electrical Engineering & Computer Science Ann ArborMI48109 United States Kth Royal Institute of Technology Electromagnetic Engineering and Fusion Science Stockholm10044 Sweden

ISBN: (纸本)9781665442282

In this communication, we present a low-dispersive leaky-wave antenna consisting of a parallel-plate-waveguide structure loaded by a modulated metasurface and a dense medium. The low-dispersive leaky-wave mode is engineered by a proper design of the metasurface and the chosen permittivity of the dense medium. The dispersion analysis is based on the transverse resonance technique and validated through full-wave simulations. A dense medium with a prism shape and a relative permittivity of 12 is used to radiate a beam pointing at 28.3° in elevation in the Ks-band (27-33 GHz) with only 0.5° variation over a 20% relative bandwidth. The leaky-wave mode supported by the structure is efficiently launched by using a compact quasi-optical system. The full antenna dimensions are 225×175×57 mm3 with an expected average gain of 27.5 dBi and total efficiency greater than 55%. © 2023 IEEE.

关键词： Permittivity

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Machine Learning-Driven Educational Ethics Considerations: Striking A Balance Between Privacy And Personalization 10

Machine Learning-Driven Educational Ethics Considerations: S...

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10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and computer engineering, UPCON 2023

作者： Siddiqua, Ayasha Sabeer, Shaista Rao, R. Suvarna Ahuja, Suniana Aggarwal, Shikha Lourens, Melanie Jazan University Dept. of Information Technology and Security Saudi Arabia Jazan University Computer Science Saudi Arabia Institute of Aeronautical Engineering Telangana Hyderabad India Lovely Professional University Phagwara India Management Institute of Technology & Science U.P. Ghaziabad India Durban University of Technology Faculty of Management Sciences South Africa

ISBN: (纸本)9798350382471

This empirical study investigates the complex trade-off between personalization and privacy in the context of education powered by machine learning. Machine learning is emerging as a transformative force in the rapidly changing field of education, offering personalized as well as adaptive learning experiences. The incorporation of algorithms that can analyze large datasets together with produce insights presents a crucial contradiction that calls for a careful analysis of ethical issues. The study explores the revolutionary possibilities of machine learning, highlighting the manner in which it can be used to customize learning environments to meet the needs of each student. It does, nonetheless, also address privacy issues resulting from large-scale data collection, archiving, and possible abuse. Using a mixed-methods approach, the analysis combines stakeholder insights and quantitative data on customized interventions. Safeguarding privacy, being transparent, as well as obtaining informed consent are essential elements in the moral application of machine learning in education. Legal alongside regulatory measures are examined, with a focus on the necessity of flexible frameworks to meet changing technological challenges. The human element offers important practical insights, as demonstrated by the viewpoints of teachers and students. In the end, this paper emphasizes the importance that it is to work together, conduct continuous ethical analysis, and be dedicated to striking a balance between innovations, privacy, alongside personalization in the constantly changing field of education. © 2023 IEEE.

关键词： Adaptive Learning Ethical Framework Machine Learning in Education Personalization Privacy Concerns

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Development of a GSM Enabled Real-Time Electronic Display Board

Development of a GSM Enabled Real-Time Electronic Display Bo...

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IEEE Power engineering Society Conference and Exposition in Africa, PowerAfrica

作者： Aiyudubie S. Uyi Abel E. Airoboman Reginald Ogu Chijioke Okwuokenye Telecommunication Engineering Dept Airforce Institute of Technology Kaduna Nigeria Department of Electrical/Electronic Engineering Nigerian Defence Academy Kaduna Nigeria Department of Computer Engineering Federal University of Technology Owerri Abuja Electric Distribution Company FCT Nigeria

ISBN: (数字)9798350389388

ISBN: (纸本)9798350389395

The development of an electronic display board that utilizes global system for mobile communications (GSM) functionalities is presented in this paper. The aim of this research was to overcome the challenges associated with the currently deployed display notice boards systems. These challenges include the enormous man power and time required to change the notice on a manual notice board and the required tedious reprogramming to change the notice on a programmable notice board. This research utilized the combined advantages of GSM and embedded system technology to eliminate these challenges. The control unit is developed with an ATMEGA328P microcontroller to control the transmission and reception of messages from the Mobile phone to a GSM900 modem. The STM32F103 microcontroller controls the display and scrolling of the messages on a P10 light-emitting diode (LED) matrix display board unit. Also, a set of instruction codes written in the object-oriented C language, programmed onto the microcontrollers provided all required functionalities of the wireless control and display of notices. Results obtained showed that information in the form of text messages can be sent from a mobile phone for display on the electronic display notice board.

关键词： GSM Embedded systems Codes Microcontrollers Manuals Light emitting diodes Modems Mobile communication Mobile handsets Real-time systems

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Hiding secret message using matrix reordering and image blocking 2

Hiding secret message using matrix reordering and image bloc...

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2nd International Conference on Secure Cyber Computing and Communications, ICSCCC 2021

作者： Mahendru, Tanisha Verma, Harsh Kumar Dr BR Ambedkar National Institute of Technology Dept of Computer Science and Engineering Jalandhar India

ISBN: (纸本)9781665444156

Image Steganography is a solitary concept of hiding a data inside the image. As there is an expansion of interconnected networks so users exchange their information over the channels but transmission is hardly secure. So there is a concept of Steganography which is a proficiency of deceptive transmission of secret deets concealed inside other media. This paper proposes a new model in which capacity of data embedding is increased by using LSB2z algorithm and security is also increased by using Matrix Reordering and Image Blocking. © 2021 IEEE.

关键词： Steganography

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Detection of Criminal Activity Using Deep Learning

Detection of Criminal Activity Using Deep Learning

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Science, technology, engineering and Management (ICSTEM), International Conference on

作者： P. Purushotham Ganja Srividya Avula Chitty Arun Kumar Kurakula Manda Silparaj Ajmeera Kiran Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Dept of CSE Stanley College ot Engineerine & Technology for Women Hyderabad VR Siddhartha Engineering College SAHE Deemed to be University Vijayawada CSE Mohan Babu University Tirupati Andhra Pradesh India Department of Computer Science and Engineering (CS) CVR College of Engineering Hyderabad

ISBN: (数字)9798350376913

ISBN: (纸本)9798350388473

The surge in criminal activities presents a formidable challenge for global law enforcement agencies. Traditional crime detection methods often struggle to address the intricate and varied nature of criminal behaviors. Many businesses deploy CCTV systems for continuous observation of people and their activities. The developed system exhibits significant potential for applications in public safety, surveillance, and law enforcement, serving as an intelligent and automated tool for early detection and prevention of criminal activities. Continuous human monitoring of data is nearly impossible due to the workforce and attention required. Automation becomes essential. The project proposed utilizes the deep learning technology, a CNN model is designed to identify harmful behaviour in the videos. To expedite the identification of abnormal events, it is crucial to automate this process, indicating which frame and segment contain the unusual activity. This involves dividing the video into frames and scrutinizing the people and activities in each processed frame. When it detects criminal activity, it can trigger alerts or notifications to the personnel, allowing them to respond promptly.

关键词： Deep learning Machine learning algorithms Law enforcement Surveillance Real-time systems Public security Security

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Brain tumor detection: An application based on machine learning 2

Brain tumor detection: An application based on machine learn...

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2nd International Conference for Emerging technology, INCET 2021

作者： Gaikwad, Sharmila Patel, Saarah Shetty, Ajinkya MCT's Rajiv Gandhi Institute of Technology Dept. of Computer Engineering Mumbai India

ISBN: (纸本)9781728170299

Since years Machine Learning have played a significant part in the healthcare sector. Out of the various deep learning approaches, Convolutional Neural Networks has shown the most promising results in the classification task. The objective of this paper was to build an application of CNN by proposing a medical expert-based approach to detect Brain Tumor. Annually thousands of people are being diagnosed with Brain Tumor and various treatments such as surgery and radiotherapy are being used currently and to detect the tumor MRI is the imaging technique widely used which is very time-consuming as tumors are highly variable in their size, shape, and structure. Also, there is a risk of human error as there may occur variations by different expert physicians leading to inaccurate results which call for the need for an automatic detection system. The proposed approach helped to classify the MRI images as tumorous and non-tumorous, restraining the visual exploration by doctors to make it less time-consuming since the methods used in the system can detect tumors with the use of MRI images. The architecture was based on CNN along with Transfer Learning model VGG-16. The proposed system contained a dataset from Kaggle which was then preprocessed followed by augmentation and passed to the architecture where it was capable of obtaining accurate results rapidly. © 2021 IEEE.

关键词： Magnetic resonance imaging

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Evaluating the Necessity of Cloud Computing in Modern Industrial Applications: A Comprehensive Analysis

Evaluating the Necessity of Cloud Computing in Modern Indust...

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Computational Intelligence, Communication technology and Networking (CICTN), International Conference on

作者： Abhiraj Singh Manish Kumar Soni Ajay Pratap Dept.of Computer Sci. & Engineering Bansal Inst of Eng. & Technology Lucknow India Amity Institute of Info Technology Amity University Lucknow Uttar Pradesh India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

This study thoroughly assesses the need for cloud computing across industries, examining the ways in which it improves scalability, flexibility, and affordability. Through the use of cloud computing, industries may update their IT infrastructure and move from outdated, capital-intensive models to more adaptable and effective cloud-based solutions. The report examines how cloud services like Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) are integrated into key industries like manufacturing, healthcare, finance, and retail. Through the implementation of cutting-edge technologies like Internet of Things (IoT), machine learning (ML), and artificial intelligence (Al), cloud computing stimulates innovation, optimizes operations, and improves decision-making via data-driven insights. The growing significance of hybrid and multi-cloud strategies—which offer increased flexibility and enable industries to optimize resources and enhance performance—is also covered in the study. The study discusses the difficulties that sectors encounter in implementing cloud computing, along with its advantages. These difficulties include worries about data security, regulatory compliance, and cloud management. Strong security frameworks and efficient governance models are highlighted as essential elements of successful cloud integration. This study presents a framework for adopting cloud-based solutions for industries and emphasizes the significance of cloud computing as a fundamental technology for contemporary industrial applications.

关键词： Industries Cloud computing Technological innovation Adaptation models Computational modeling Software as a service Finance Medical services Manufacturing Internet of Things

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A Novel Design of Secured BlockChain Assisted Land Registration Mechanism by using Enhanced Verification Principles

A Novel Design of Secured BlockChain Assisted Land Registrat...

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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Prabu, R.T. Hemalatha, R. Madhini, M. Diwakaran, S. Senthilkumar, V. Thiyaneswaran, B. Dept. Electronics and Communication Saveetha School of Engineering Chennai India Dept. Computer Science Engineering St.Joseph College of Engineering Chennai India Dept. Electronics and Communication S.A.Engineering College Chennai India Dept. Master of Comp. Applns Kalasalingam Academy of Res. & Edn. Srivilliputhur India Department of Data Science VelTech Multitech Engg. College Chennai India Dept. Electronics & Communication Sona College of Technology Salem India

ISBN: (纸本)9798350305708

In the contemporary world, safeguarding data has assumed paramount importance, prompting numerous industrial sectors to fortify their defenses against potential hackers. In this landscape, blockchain has emerged as a cutting-edge technology that empowers peers to securely exchange various assets, including currency, financial documents, and land properties. Operating as an open-source public network, blockchain eliminates the need for a central authority. Instead, it facilitates peer-to-peer interactions, ensuring that transactions, value transfers, and data sharing are authenticated by all interconnected nodes within the network. The conventional process of land registration, characterized by its sluggishness and complexity, involves multiple intermediaries and is susceptible to instances of fraudulent and counterfeit land transfers. To address these challenges, the paper introduces a conceptual framework for blockchain-based land registry systems. By analyzing existing frameworks and scrutinizing the robust strategies and concepts they employ, the paper establishes connections that culminate in the creation of this conceptual framework. The proposed solution in the paper revolves around the secure transfer of land ownership through blockchain technology. This solution circumvents the need for intermediaries, allowing buyers and sellers to conduct land ownership transactions seamlessly using the Ethereum network. By leveraging the power of blockchain, this solution aims to mitigate the vulnerabilities and inefficiencies inherent in traditional land registration processes, ushering in a more secure, efficient, and transparent approach to managing land ownership transactions. © 2023 IEEE.

关键词： Blockchain Land Registration land registry systems

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